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Privacy Preserving Data Mining(PPDM) is a rising field of research in Data Mining and various approaches are being introduced by the researchers. One of the approaches is a sanitization process, that transforms the source database into a modified one by removing selective items so that the counterparts or adversaries cannot extract the hidden patterns from. This study address this concept and proposes a revised Item-based Maxcover Algorithm(IMA) which is aimed at less information loss in the large databases with minimal removal of items.

An improved Item-based Maxcover Algorithm to protect Sensitive Patterns in Large Databases